Whisper Large v3 Fine-Tuned Finnish - CommonVoice13
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3318
- Wer: 25.9893
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 800
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.3591 | 0.42 | 50 | 0.3653 | 32.0541 |
| 0.4623 | 0.84 | 100 | 0.4383 | 35.4316 |
| 0.3229 | 1.26 | 150 | 0.4386 | 35.3672 |
| 0.2538 | 1.68 | 200 | 0.4324 | 34.4929 |
| 0.1972 | 2.11 | 250 | 0.4287 | 34.4561 |
| 0.1194 | 2.53 | 300 | 0.4235 | 33.6094 |
| 0.1132 | 2.95 | 350 | 0.3826 | 30.1767 |
| 0.0669 | 3.37 | 400 | 0.4073 | 33.0941 |
| 0.0614 | 3.79 | 450 | 0.3869 | 29.5233 |
| 0.0435 | 4.21 | 500 | 0.3942 | 30.1859 |
| 0.032 | 4.63 | 550 | 0.3839 | 27.9404 |
| 0.0184 | 5.05 | 600 | 0.3571 | 25.7500 |
| 0.0094 | 5.47 | 650 | 0.3477 | 25.8605 |
| 0.0055 | 5.89 | 700 | 0.3371 | 26.6243 |
| 0.0026 | 6.32 | 750 | 0.3329 | 25.4463 |
| 0.0015 | 6.74 | 800 | 0.3318 | 25.9893 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
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